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Frequency tracking of atrial fibrillation using hidden Markov models

Publiceringsår: 2006
Språk: Engelska
Sidor: 1406-1409
Publikation/Tidskrift/Serie: IEEE Press
Dokumenttyp: Konferensbidrag

Sammanfattning

A Hidden Markov Model (HMM) is used to improve the robustness to noise when tracking the atrial fibrillation (AF) frequency in the ECG. Each frequency interval corresponds to a state in the HMM. Following QRST cancellation, a sequence of observed states is obtained from the residual ECG, using the short time Fourier transform. Based on the observed state sequence, the Viterbi algorithm, which uses a state transition matrix, an observation matrix and an initial state vector, is employed to obtain the optimal state sequence. The state transition matrix incorporates knowledge of intrinsic AF characteristics, e.g., frequency variability, while the observation matrix incorporates knowledge of the frequency estimation method and SNRs. An evaluation is performed using simulated AF signals where noise obtained from ECG recordings have been added at different SNR. The results show that the use of HMM considerably reduces the average RMS error associated with the frequency tracking: at 5 dB SNR the RMS error drops from 1.2 Hz to 0.2 Hz.

Disputation

Nyckelord

  • Technology and Engineering

Övriga

28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS '06.
2006-08-30/2006-09-03
New York, USA
Published
Yes
"©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE."
  • ISSN: 1557-170X
  • ISBN: 1-4244-0032-5

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